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Conference on computer vision and pattern recognition (CVPR)

作者： Peng Wang Christian Kohler Ragini Verma Department of Radiology University of Pennsylvania Philadelphia PA USA Department of Psychiatry University of Pennsylvania Philadelphia PA USA

Although it is usually assumed in many pattern recognition problems that different patterns are distinguishable, some patterns may have inseparable overlap. For example, some facial expressions involve subtle muscle movements, and are difficult to separate from other expressions or neutral faces. In this paper, we consider such overlapped patterns as "clusters", and present a novel method to quantify cluster overlap based on the Bayes error estimation on manifolds. Our method first applies a manifold learning method, ISOMAP, to discover the intrinsic structure of data, and then measures the overlap of different clusters using the k-NN Bayes error estimation on the learned manifolds. Due to the ISOMAP"s capability of preserving geodesic distances and k-NN's localized estimation, the method can provide an accurate measure of the overlap between clusters, as demonstrated by our simulation experiments. The method is further applied for an analysis of a specific type of facial expression impairment in schizophrenia, i.e.,"flat effect", which refers to a severe reduction in emotional expressiveness. In this study, we capture facial expressions of individuals, and quantify their expression flatness by estimating overlap between different facial expressions. The experimental results show that the patient group has much larger facial expression overlap than the control group, and demonstrate that the flat affect is an important symptom in diagnosing schizophrenia patients.

关键词： Error analysis Learning systems Level measurement Data mining Radiology Psychiatry pattern recognition Muscles Uncertainty Distance measurement

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Mumford-Shah Meets Stereo: Integration of Weak Depth Hypotheses

Mumford-Shah Meets Stereo: Integration of Weak Depth Hypothe...

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Conference on computer vision and pattern recognition (CVPR)

作者： Thomas Pock Christopher Zach Horst Bischof Institute for Computer Graphics and Vision Graz University of Technology Graz Austria VRVis Research Center Graz Austria

Recent results on stereo indicate that an accurate segmentation is crucial for obtaining faithful depth maps. Variational methods have successfully been applied to both image segmentation and computational stereo. In this paper we propose a combination in a unified framework. In particular, we use a Mumford-Shah-like functional to compute a piecewise smooth depth map of a stereo pair. Our approach has two novel features: First, the regularization term of the functional combines edge information obtained from the color segmentation with flow-driven depth discontinuities emerging during the optimization procedure. Second, we propose a robust data term which adoptively selects the best matches obtained from different weak stereo algorithms. We integrate these features in a theoretically consistent framework. The final depth map is the minimizer of the energy functional, which can be solved by the associated functional derivatives. The underlying numerical scheme allows an efficient implementation on modern graphics hardware. We illustrate the performance of our algorithm using the Middlebury database as well as on real imagery.

关键词： Image segmentation Robustness Markov random fields computer graphics Hardware Optimization methods Image edge detection Shape Image databases Spatial databases

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Layered Depth Panoramas

Layered Depth Panoramas

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Conference on computer vision and pattern recognition (CVPR)

作者： Ke Colin Zheng Sing Bing Kang Michael F. Cohen Richard Szeliski University of Washington Seattle WA USA Microsoft Research Limited Redmond WA USA

Representations for interactive photorealistic visualization of scenes range from compact 2D panoramas to data-intensive 4D light fields. In this paper, we propose a technique for creating a layered representation from a sparse set of images taken with a hand-held camera. This representation, which we call a layered depth panorama (LDP), allows the user to experience 3D by off-axis panning. It combines the compelling experience of panoramas with limited 3D navigation. Our choice of representation is motivated by ease of capture and compactness. We formulate the problem of constructing the LDP as the recovery of color and geometry in a multi-perspective cylindrical disparity space. We leverage a graph cut approach to sequentially determine the disparity and color of each layer using multi-view stereo. Geometry visible through the cracks at depth discontinuities in a frontmost layer is determined and assigned to layers behind the frontmost layer. All layers are then used to render novel panoramic views with parallax. We demonstrate our approach on a variety of complex outdoor and indoor scenes.

关键词： Layout Cameras Rendering (computer graphics) Geometry Image reconstruction Solid modeling Visualization Image storage Costs computer vision

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Real-time Object Classification in Video Surveillance Based on Appearance Learning

Real-time Object Classification in Video Surveillance Based ...

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Conference on computer vision and pattern recognition (CVPR)

作者： Lun Zhang Stan Z. Li Xiaotong Yuan Shiming Xiang Center for Biometrics and Security Research & National Laboratory of Pattern Recognition Institute of Automation Chinese Academy and Sciences Beijing China

Classifying moving objects to semantically meaningful categories is important for automatic visual surveillance. However, this is a challenging problem due to the factors related to the limited object size, large intra-class variations of objects in a same class owing to different viewing angles and lighting, and real-time performance requirement in real-world applications. This paper describes an appearance-based method to achieve real-time and robust objects classification in diverse camera viewing angles. A new descriptor, i.e., the multi-block local binary pattern (MB-LBP), is proposed to capture the large-scale structures in object appearances. Based on MB-LBP features, an adaBoost algorithm is introduced to select a subset of discriminative features as well as construct the strong two-class classifier. To deal with the non-metric feature value of MB-LBP features, a multi-branch regression tree is developed as the weak classifiers of the boosting. Finally, the error correcting output code (ECOC) is introduced to achieve robust multi-class classification performance. Experimental results show that our approach can achieve real-time and robust object classification in diverse scenes.

关键词： Video surveillance Cameras Robustness Vehicles Classification tree analysis Layout Object recognition Shape Large-scale systems Error correction codes

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INSPECTION OF METALLIC STAMPED PARTS USING AN IMAGE FUSION TECHNIQUE

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IFAC Proceedings Volumes 2007年第3期40卷 177-182页

作者： Eusebio de la Fuente López Félix Miguel Trespaderne

This paper presents a machine vision system for on-line inspection of large stamped car parts. The vision system includes a CCD camera and an illumination device that permit to obtain two images of the same zone illuminated from two different directions. The acquired images are fused using an energy function in order to eliminate the spurious features originated by glints and shadows of the metallic surface. The defects, if they are present, remain in the fused image and can easily be pointed out.

关键词： computer vision visual pattern recognition quality control

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Design and simulation of the Positioning System Using computer vision for IC Packaging

Design and simulation of the Positioning System Using Comput...

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第八届电子封装技术国际会议(2007 8th International Conference on Electronics Packaging Technology ICEPT2007)

作者： Junlan Li Yizhong Wang Dawei Zhang Xingyu Zhao Department of Mechanical Engineering Tianjin University Tianjin 300072 China

A positioning system using computer vision technologies is designed to obtain high precision during wire bonding. The main processes are on-line examining the position of a chip before bonding, calculating its locating errors, and cooperating with control system to eliminate these ***, chips' accurate positions can be obtained which can improve the technology of wire bonding. A novel optical imaging system is designed to get images with high ***-imaging system consists of two lenses to achieve appropriate magnifying multiple and working distance, which are 4 and distance is 47mm, respectively. Illumination lens provides steady and symmetrical lighting condition on working area. Normalized correlation image registration algorithm is applied as the pattern recognition positioning algorithm of wire bonder's vision system. Some simulation experiments have been carried out, which show that the precision of pattern recognition in this system is 3.5μm, which satisfies the requirements of wire bonding.

关键词： Computational modeling computer simulation computer vision Integrated circuit packaging Bonding Wire computer errors Error correction Lenses pattern recognition

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Bilattice-based Logical Reasoning for Human Detection

Bilattice-based Logical Reasoning for Human Detection

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Conference on computer vision and pattern recognition (CVPR)

作者： Vinay D. Shet Jan Neumann Visvanathan Ramesh Larry S. Davis Siemens Corporate Research Inc. Princeton NJ USA Computer Vision Laboratory University of Maryland College Park MD USA

The capacity to robustly detect humans in video is a critical component of automated visual surveillance systems. This paper describes a bilattice based logical reasoning approach that exploits contextual information and knowledge about interactions between humans, and augments it with the output of different low level detectors for human detection. Detections from low level parts-based detectors are treated as logical facts and used to reason explicitly about the presence or absence of humans in the scene. Positive and negative information from different sources, as well as uncertainties from detections and logical rules, are integrated within the bilattice framework. This approach also generates proofs or justifications for each hypothesis it proposes. These justifications (or lack thereof) are further employed by the system to explain and validate, or reject potential hypotheses. This allows the system to explicitly reason about complex interactions between humans and handle occlusions. These proofs are also available to the end user as an explanation of why the system thinks a particular hypothesis is actually a human. We employ a boosted cascade of gradient histograms based detector to detect individual body parts. We have applied this framework to analyze the presence of humans in static images from different datasets.

关键词： Humans Detectors Layout Geometry Educational institutions computer vision Robustness Surveillance Uncertainty Histograms

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SVM Based Scheme for Thai and English Script Identification

SVM Based Scheme for Thai and English Script Identification

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International Conference on Document Analysis and recognition

作者： S. Chanda O.R. Terrades U. Pal Indian Statistical Institute Computer Vision and Pattern Recognition Unit Kolkata India Computer Vision Center Universitat Authnòma de Barcelona Barcelona Spain

In some Thai documents, a single text line of a document page may contain both Thai and English scripts. For the optical character recognition (OCR) of such a document page it is better to identify, at first, Thai and English script portions and then to use individual OCR system of the respective scripts on these identified portions. In this paper, a SVM based method is proposed for identification of word-wise printed English and Thai scripts from a single line of a document page. Here, at first, the document is segmented into lines and then lines are segmented into character groups (words). In the proposed scheme, we identify the script of the individual character group combining different character features obtained from structural shape, profile, component overlapping information, topological properties, water reservoir concept etc. Based on the experiment on 6110 data we obtained 99.36% script identification accuracy from the proposed scheme.

关键词： Support vector machines Optical character recognition software Support vector machine classification computer vision Optical network units Structural shapes Water resources Reservoirs Neural networks pattern recognition

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Graph Cut Based Optimization for MRFs with Truncated Convex Priors

Graph Cut Based Optimization for MRFs with Truncated Convex ...

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Conference on computer vision and pattern recognition (CVPR)

作者： Olga Veksler University of Western Ontario London Canada

Optimization with graph cuts became very popular in recent years. Progress in problems such as stereo correspondence, image segmentation, etc., can be attributed, in part, to the development of efficient graph cut based optimization. Recent evaluation of optimization techniques shows that the popular expansion and swap graph cut algorithms perform extremely well for energies where the underlying MRF has the Potts prior, which corresponds to the assumption that the true labeling is piecewise constant. For more general priors, however, such as corresponding to piece-wise smoothness assumption, both swap and expansion algorithms do not perform as well. We develop several optimization algorithms for truncated convex priors, which imply piecewise smoothness assumption. Both expansion and swap algorithms are based on moves that give each pixel a choice of only two labels. Our insight is that to obtain a good approximation under piecewise smoothness assumption, a pixel should have a choice among more than two labels. We develop new "range" moves which act on a larger set of labels than the expansion and swap algorithms. We evaluate our method on problems of image restoration, in-painting, and stereo correspondence. Our results show that we are able to get more accurate answers, both in terms of the energy, which is the direct goal, and in terms of accuracy, which is an indirect, but more important goal.

关键词： Labeling Image segmentation Image restoration Stereo vision Performance evaluation Computational modeling Simulated annealing computer vision computer graphics Stereo image processing

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Compositional Boosting for Computing Hierarchical Image Structures

Compositional Boosting for Computing Hierarchical Image Stru...

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Conference on computer vision and pattern recognition (CVPR)

作者： Tian-Fu Wu Gui-Song Xia Song-Chun Zhu Lotus Hill Institute of Computer Vision and Information Science Ezhou China Statistics Department University of California Los Angeles CA USA

In this paper, we present a compositional boosting algorithm for detecting and recognizing 17 common image structures in low-middle level vision tasks. These structures, called "graphlets", are the most frequently occurring primitives, junctions and composite junctions in natural images, and are arranged in a 3-layer And-Or graph representation. In this hierarchic model, larger graphlets are decomposed (in And-nodes) into smaller graphlets in multiple alternative ways (at Or-nodes), and parts are shared and re-used between graphlets. Then we present a compositional boosting algorithm for computing the 17 graphlets categories collectively in the Bayesian framework. The algorithm runs recursively for each node A in the And-Or graph and iterates between two steps -bottom-up proposal and top-down validation. The bottom-up step includes two types of boosting methods, (i) Detecting instances of A (often in low resolutions) using Adaboosting method through a sequence of tests (weak classifiers) image feature, (ii) Proposing instances of A (often in high resolution) by binding existing children nodes of A through a sequence of compatibility tests on their attributes (e.g angles, relative size etc). The Adaboosting and binding methods generate a number of candidates for node A which are verified by a top-down process in a way similar to Data-Driven Markov Chain Monte Carlo [18]. Both the Adaboosting and binding methods are trained off-line for each graphlet category, and the compositional nature of the model means the algorithm is recursive and can be learned from a small training set. We apply this algorithm to a wide range of indoor and outdoor images with satisfactory results.

关键词： Boosting Testing Image edge detection Image resolution Image segmentation computer vision Image recognition Bayesian methods Proposals Inference algorithms

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